The Automation of Advertising

As I explained in The Consumer Trap book, modern Big Business Marketing is a logical and historical extension of Frederick Winslow Taylor’s principles of scientific management. What Taylor grew famous for teaching early corporate barons to do to the paid-labor process, latter-day corporate planners do to the off-the-job experiences of their prospective customers.

So, it is only natural that all the same extensions that have swept modern capitalist labor-process design will eventually also occur within the competitively expanding BBM process.

ONLINE advertisers are not lacking in choices: They can display their ads in any color, on any site, with any message, to any audience, with any image.

Now, a new breed of companies is trying to tackle all of those options and determine what ad works for a specific audience. They are creating hundreds of versions of clients’ online ads, changing elements like color, type font, message, and image to see what combination draws clicks on a particular site or from a specific audience.

It is technology that could cause a shift in the advertising world. The creators and designers of ads have long believed that a clever idea or emotional resonance drives an ad’s success. But that argument may be difficult to make when analysis suggests that it is not an ad’s brilliant tagline but its pale-yellow background and sans serif font that attracts customers.

The question is, “how do we combine creative energy, which is a manual and sort of qualitative exercise, with the raw processing power of computing, which is all about quantitative data?” said Tim Hanlon, executive vice president of VivaKi Ventures, the investment unit of Publicis Groupe.

The push to automate the creative elements of ad units is coming from two companies in California, not Madison Avenue.

Adisn, based in Long Beach, and Tumri, based in Mountain View, are working both sides of the ad equation. On one, they are trying to figure out who is looking at a page by using a mix of behavioral targeting and analysis of the page’s content. On the other side, they are assembling an ad on the fly that is meant to appeal to that person.

Both companies assume there is no perfect version of an ad, and instead assemble hundreds of different versions that are displayed on Web sites where their clients have bought ad space, showing versions of an ad to actual consumers as they browse the Web.

That might lead to finding that an ad for a baby supply store is more popular with young mothers when it features a bottle instead of diapers.

(Adisn and Tumri both measure the ad’s effectiveness based on parameters the advertiser sets, like how many people clicked on the ad or how many people actually bought something after clicking on it. They compare those with standard ads they run as part of a control group.)

Adisn’s approach has been to build a database of related words so it can assess the content of a Web site or blog based on the words on its pages.

Based on that analysis, Adisn’s system pulls different components — actors, fonts, background images — to make an ad. For example, it might show an ad with a blue background, an image of a beach, and a text about tickets to Hawaii. “Once we’ve built this huge database of hundreds of millions of relationships” between words, said Andy Moeck, the chief executive of Adisn, the system can “make a very good real-time decision as to what is the most relevant or appropriate campaign we could show.”